Buildability / Receipt
This public receipt window renders only fields present in the canonical receipt object, deterministic fixture receipt, or canonical evidence receipt. Missing compute, demo, hash, signature, approval, telemetry, and adoption fields stay explicit.
Public buildability page receipt window
/buildability/rethinking-agentic-reinforcement-learning-in-large-language-models
Subject: Rethinking Agentic Reinforcement Learning In Large Language Models
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Data
{"file name": "input.pdf", "number of pages": 17, "author": "Fangming Cui; Ruixiao Zhu; Cheng Fang; Sunan Li; Jiahong Li"
Truth Boundary
Buildability surfaces only report computed viability and proof receipts. They do not claim live production usage, pilot outcomes, founder sign-off, public Brier calibration, judge divergence, or external adoption unless explicitly sourced.
Compute
{"file name": "input.pdf", "number of pages": 17, "author": "Fangming Cui; Ruixiao Zhu; Cheng Fang; Sunan Li; Jiahong Li", "title": "Rethinking Agentic Reinforcement Learning In Large Language Models", "creation date": "D:20260501005958+00'00'", "modification date": "D:20260501005958+00'00'", "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 17, "author": "Fangming Cui; Ruixiao Zhu; Cheng Fang; Sunan Li; Jiahong Li", "title": "Rethinking Agentic Reinforcement Learning In Large Language Models", "creation date": "D:20260501005958+00'00'", "modification date": "D:20260501005958+00'00'", "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 17, "author": "Fangming Cui; Ruixiao Zhu; Cheng Fang; Sunan Li; Jiahong Li", "title": "Rethinking Agentic Reinforcement Learning In Large Language Models", "creation date": "D:20260501005958+00'00'", "modification date": "D:20260501005958+00'00'", "kids": []}
Receipt path
/buildability/rethinking-agentic-reinforcement-learning-in-large-language-models
Paper ref
rethinking-agentic-reinforcement-learning-in-large-language-models
arXiv id
2604.27859
Generated at
2026-05-01T15:05:50.006Z
Evidence freshness
stale
Last verification
2026-05-01T15:05:50.006Z
Sources
3
References
0
Coverage
50%
Lineage hash
9d72acd75789c4a79d53ec0f8c6c6b0ab00ebcab497dc93cc90f248def1dde23
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Some score or evidence fields are outside the preferred freshness window.
repo_url
references